Large Foundation Model for Cancer Segmentation
Zeyu Ren, Yudong Zhang, Shuihua Wang
Abstract
Recently, large language models such as ChatGPT have made huge strides in understanding and generating human-like text and have demonstrated considerable success in natural language processing. These foundation models also perform well in computer vision. However, there is a growing need to use these technologies for specific medical tasks, especially for identifying cancer in images. This paper looks at how these foundation models, such as the segment anything model, could be used for cancer segmentation, discussing the potential benefits and challenges of applying large foundation models to help with cancer diagnoses.
Topics & Concepts
Foundation (evidence)SegmentationComputer scienceArtificial intelligenceMedical diagnosisCancerData scienceMachine learningMedicinePathologyGeographyArchaeologyInternal medicineRadiomics and Machine Learning in Medical ImagingAI in cancer detectionCOVID-19 diagnosis using AI